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Computer Science > Software Engineering

arXiv:2401.09885 (cs)
[Submitted on 18 Jan 2024 (v1), last revised 6 Feb 2024 (this version, v3)]

Title:Source Code Clone Detection Using Unsupervised Similarity Measures

Authors:Jorge Martinez-Gil
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Abstract:Assessing similarity in source code has gained significant attention in recent years due to its importance in software engineering tasks such as clone detection and code search and recommendation. This work presents a comparative analysis of unsupervised similarity measures for identifying source code clone detection. The goal is to overview the current state-of-the-art techniques, their strengths, and weaknesses. To do that, we compile the existing unsupervised strategies and evaluate their performance on a benchmark dataset to guide software engineers in selecting appropriate methods for their specific use cases. The source code of this study is available at this https URL
Comments: Accepted for publication as Full Paper in the Software Quality Days 2024, Vienna, Austria
Subjects: Software Engineering (cs.SE); Information Retrieval (cs.IR)
Cite as: arXiv:2401.09885 [cs.SE]
  (or arXiv:2401.09885v3 [cs.SE] for this version)
  https://doi.org/10.48550/arXiv.2401.09885
Related DOI: https://doi.org/10.1007/978-3-031-56281-5_2

Submission history

From: Jorge Martinez Gil Ph.D. [view email]
[v1] Thu, 18 Jan 2024 10:56:27 UTC (292 KB)
[v2] Fri, 19 Jan 2024 07:23:04 UTC (292 KB)
[v3] Tue, 6 Feb 2024 15:09:13 UTC (162 KB)
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